Factors relevant to a return to work: a multivariate approach.

Area of Science:

• Occupational Health
• Psychosocial Medicine
• Rehabilitation Science

Background:

• Understanding factors influencing return to work (RTW) is crucial for managing sick leave.
• Early identification of individuals at risk of prolonged sick leave is needed.
• Previous research often focused on isolated factors, limiting predictive power.

Purpose of the Study:

• To identify significant factors for returning to work after a period of sick leave.
• To determine if these factors can be used early in sick leave to predict work outcomes.
• To explore the utility of a multivariate approach for predicting long-term sick leave outcomes.

Main Methods:

• Multivariate Partial Least Squares (PLS) of Latent Structures analysis was employed.
• Data collected via questionnaire included socio-demographics, symptoms, daily life consequences, expectations, and psychosocial factors.
• Analysis included 121 adults (18-64 years) on sick leave, irrespective of diagnosis, and four-year sickness incidence data.

Main Results:

• A reliable prediction of return to work necessitates a combination of multiple factors.
• Individual psychosocial instruments are not effective when used in isolation.
• Strongest predictors identified: individual expectations, past sick leave duration, somatic disorders, life satisfaction, and sense of coherence.

Conclusions:

• A multivariate approach, such as PLS, is effective for predicting long-term outcomes early in sick leave.
• Predicting return to work requires integrating diverse factors, not relying on isolated measures.
• The study highlights key individual and health-related factors that significantly influence return to work trajectories.